Developing Data Models with LookML
Earned Jun 14, 2023 EDT
Analyzing and Visualizing Data in Looker
Earned May 28, 2023 EDT
Applying Machine Learning to your Data with Google Cloud
Earned May 26, 2023 EDT
Achieving Advanced Insights with BigQuery
Earned May 21, 2023 EDT
Creating New BigQuery Datasets and Visualizing Insights
Earned May 18, 2023 EDT
Google Cloud Big Data and Machine Learning Fundamentals
Earned May 15, 2023 EDT
Machine Learning is essential to many modern applications nowadays. At the same time, expectations towards ML capabilities and thus complexity & size of ML models and datasets grows rapidly. In this game, you’ll experiment hands-on with how to scale ML “like Google” to iterate quickly on complex ML challenges and take your ML tasks to the next level.
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This course empowers you to develop scalable, performant LookML (Looker Modeling Language) models that provide your business users with the standardized, ready-to-use data that they need to answer their questions. Upon completing this course, you will be able to start building and maintaining LookML models to curate and manage data in your organization’s Looker instance.
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In this course, you learn how to do the kind of data exploration and analysis in Looker that would formerly be done primarily by SQL developers or analysts. Upon completion of this course, you will be able to leverage Looker's modern analytics platform to find and explore relevant content in your organization’s Looker instance, ask questions of your data, create new metrics as needed, and build and share visualizations and dashboards to facilitate data-driven decision making.
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In this course, we define what machine learning is and how it can benefit your business. You'll see a few demos of ML in action and learn key ML terms like instances, features, and labels. In the interactive labs, you will practice invoking the pretrained ML APIs available as well as build your own Machine Learning models using just SQL with BigQuery ML.
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The third course in this course series is Achieving Advanced Insights with BigQuery. Here we will build on your growing knowledge of SQL as we dive into advanced functions and how to break apart a complex query into manageable steps.
We will cover the internal architecture of BigQuery (column-based sharded storage) and advanced SQL topics like nested and repeated fields through the use of Arrays and Structs. Lastly we will dive into optimizing your queries for performance and how you can secure your data through authorized views.
After completing this course, enroll in the Applying Machine Learning to your Data with Google Cloud course.
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This is the second course in the Data to Insights course series. Here we will cover how to ingest new external datasets into BigQuery and visualize them with Looker Studio. We will also cover intermediate SQL concepts like multi-table JOINs and UNIONs which will allow you to analyze data across multiple data sources.
Note: Even if you have a background in SQL, there are BigQuery specifics (like handling query cache and table wildcards) that may be new to you.
After completing this course, enroll in the Achieving Advanced Insights with BigQuery course.
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This course introduces the Google Cloud big data and machine learning products and services that support the data-to-AI lifecycle. It explores the processes, challenges, and benefits of building a big data pipeline and machine learning models with Vertex AI on Google Cloud.
Cloud Hero: Scalable ML
Earned Jul 24, 2024 EDT
Developing Data Models with LookML
Earned Jun 14, 2023 EDT
Analyzing and Visualizing Data in Looker
Earned May 28, 2023 EDT
Applying Machine Learning to your Data with Google Cloud
Earned May 26, 2023 EDT
Achieving Advanced Insights with BigQuery
Earned May 21, 2023 EDT
Creating New BigQuery Datasets and Visualizing Insights
Earned May 18, 2023 EDT
Google Cloud Big Data and Machine Learning Fundamentals
Earned May 15, 2023 EDT